Schizophrenia is a serious mental illness that causes great harm to patients, so timely and accurate detection is essential. This study aimed to identify a better feature to represent ...electroencephalography (EEG) signals and improve the classification accuracy of patients with schizophrenia and healthy controls by using EEG signals. Our research method involves two steps. First, the EEG time series is preprocessed, and the extracted time-domain and frequency-domain features are transformed into a sequence of red-green-blue (RGB) images that carry spatial information. Second, we construct hybrid deep neural networks (DNNs) that combine convolution neural networks and long short-term memory to address RGB images to classify schizophrenic patients and healthy controls. The results show that the fuzzy entropy (FuzzyEn) feature is more significant than the fast Fourier transform (FFT) feature in brain topography. The deep learning (DL) method that we propose achieves an average accuracy of 99.22% with FuzzyEn and an average accuracy of 96.34% with FFT. These results show that the best effect is to extract fuzzy features as input features from EEG time series and then use a hybrid DNN for classification. Compared with the most advanced methods in this field, significant improvements have been achieved.
Electrochemical reduction of CO2 (CO2RR) into value‐added products is a promising strategy to reduce energy consumption and solve environmental issues. Formic acid/formate is one of the high‐value, ...easy‐to‐collect, and economically viable products. Herein, the reconstructed Bi2O2CO3 nanosheets (BOCR NSs) are synthesized by an in situ electrochemical anion exchange strategy from Bi2O2SO4 as a pre‐catalyst. The BOCR NSs achieve a high formate Faradaic efficiency (FEformate) of 95.7% at −1.1 V versus reversible hydrogen electrode (vs. RHE), and maintain FEformate above 90% in a wide potential range from −0.8 to −1.5 V in H‐cell. The in situ spectroscopic studies reveal that the obtained BOCR NSs undergo the anion exchange from Bi2O2SO4 to Bi2O2CO3 and further promote the self‐reduction to metallic Bi to construct Bi/BiO active site to facilitate the formation of OCHO* intermediate. This result demonstrates anion exchange strategy can be used to rational design high performance of the catalysts toward CO2RR.
The reconstructed BOCR derived from Bi2O2SO4 by in situ electrochemical anion exchange achieves a high selectivity toward electrochemical reduction of CO2‐to‐formate. The anion exchange promotes the self‐reduction of the catalyst to metallic Bi to construct Bi/BiO active site to facilitate the formation of OCHO* intermediate.
Reasonable design and controllable synthesis of non-Pt catalysts with high methanol oxidation activity are regarded as a valid way to promote the large-scale commercial applications of direct ...methanol fuel cells (DMFCs). Herein, we develop a convenient and cost-effective approach to the successful fabrication of nanosized Rh grown on single-walled carbon nanohorns (Rh/SWCNH) as anode catalysts for DMFCs. The unique architectural configuration endows the as-obtained hybrids with a series of intriguing structural merits, including large specific surface areas, abundant opened holes, optimized electronic structures, homogeneous Rh dispersion, and good electrical conductivity. As a consequence, the resulting Rh/SWCNH catalysts exhibit exceptional electrocatalytic properties in terms of a large electrochemically active surface area of 102.5 m
2
·g
−1
, a high mass activity of 784.0 mA·mg
−1
, as well as reliable long-term durability towards the methanol oxidation reaction in alkaline media, thereby holding great potential as alternatives for commercial Pt/carbon black and Pd/carbon black catalysts.
Graphic abstract
There are many challenges in the task of predicting ore deposits from big data repositories. The data are inherently complex and of great significance to the intervenient spatial relevance of ...deposits. The characteristics of the data make it difficult to use machine learning algorithms for the quantitative prediction of mineral resources. There are considerable interest and value in extracting spatial distribution characteristics from two-dimensional (2-d) ore-controlling factor layers under different metallogenic conditions. In this paper we undertake such analysis using a deep convolutional neural network algorithm named AlexNet. Training on the 2-d mineral prediction and classification model is performed using data from the Songtao–Huayuan sedimentary manganese deposit. It mines the coupling correlation between the spatial distribution of chemical elements, sedimentary facies, the outcrop of Datangpo Formation, faults, water system, and the areas where manganese ore bodies are present, as well as the correlation among different ore-controlling factors by employing the AlexNet networks. By comparing the training loss, training accuracy, verification accuracy, and recall of models trained by different scales of grids and different combinations of ore-controlling factor layers, we further discuss the most appropriate scale division and the optimal combination of ore-controlling factors to make the model achieve its strongest robustness. It is found that the prediction performance of AlexNet networks reaches its peak when selecting a grid division of 200 pixels × 200 pixels (the actual distance is 10 km × 10 km) and inputting the distribution layers of 21 chemical elements maps, lithofacies–paleogeographic map, formation and tectonic map, outcrop map of Datangpo Formation, and water system map. The training loss, training accuracy, verification accuracy, and recall of the optimal model are 0.0000001, 100.00%, 86.21%, and 91.67%, respectively. The proposed method is successfully applied to the 2-d metallogenic prediction in Songtao–Huayuan study area. And five metallogenic prospective areas from A to E are delineated with large probability for potential ore bodies.
Brassinosteroids (BRs) regulate plant development and stress response. Although much has been learned about their roles in plant development, the mechanisms by which BRs regulate plant stress ...tolerance remain unclear. Chilling is a major stress that adversely affects plant growth. Here, we report that BR positively regulates chilling tolerance in tomato. BR partial deficiency aggravated chilling‐induced oxidized protein accumulation, membrane lipid peroxidation, and decrease of maximum quantum efficiency of photosystem II (Fv/Fm). By contrast, overexpression of BR biosynthetic gene Dwarf or treatment with 24‐epibrassinolide (EBR) attenuated chilling‐induced oxidative damages and resulted in an increase of Fv/Fm. BR increased transcripts of RESPIRATORY BURST OXIDASE HOMOLOG1 (RBOH1) and GLUTAREDOXIN (GRX) genes, and BR‐induced chilling tolerance was associated with an increase in the ratio of reduced/oxidized 2‐cysteine peroxiredoxin (2‐Cys Prx) and activation of antioxidant enzymes. However, RBOH1‐RNAi plants failed to respond to EBR as regards to the induction of GRX genes, activation of antioxidant capacity, and attenuation of chilling‐induced oxidative damages. Furthermore, silencing of GRXS12 and S14 compromised EBR‐induced increases in the ratio of reduced/oxidized 2‐Cys Prx and activities of antioxidant enzymes. Our study suggests that BR enhances chilling tolerance through a signalling cascade involving RBOH1, GRXs, and 2‐Cys Prx in tomato.
BRs confer plant tolerance to a range of stresses, whereas the mechanisms underlie remain unclear. Plant endogenous BR levels positively regulate chilling tolerance in tomato. BR‐induced chilling tolerance is well associated with an increase in the ratio of 2‐Cys peroxiredoxin monomer to dimer and enhancement of activities of antioxidant enzymes. The apoplastic H2O2‐glutaredoxin 12/14 signalling cascade is involved in BR‐induced chilling tolerance.
Human-sensitive mechanosensation depends on ionic currents controlled by skin mechanoreceptors. Inspired by the sensory behavior of skin, we investigate zwitterionic hydrogels that generate ions ...under an applied force in a mobile-ion-free system. Within this system, water dissociates as the distance between zwitterions reduces under an applied pressure. Meanwhile, zwitterionic segments can provide migration channels for the generated ions, significantly facilitating ion transport. These combined effects endow a mobile-ion-free zwitterionic skin sensor with sensitive transduction of pressure into ionic currents, achieving a sensitivity up to five times that of nonionic hydrogels. The signal response time, which relies on the crosslinking degree of the zwitterionic hydrogel, was ~38 ms, comparable to that of natural skin. The skin sensor was incorporated into a universal throat-worn silent-speech recognition system that transforms the tiny signals of laryngeal mechanical vibrations into silent speech.
Epithelial-to-mesenchymal transition (EMT) endows epithelial cells with enhanced motility and invasiveness, allowing them to participate in many physiological and pathological processes. ...Epithelial-to-mesenchymal transition contributes to the generation of circulating tumor cells (CTCs) in epithelial cancers because it increases tumor cell invasiveness, promotes tumor cell intravasation and ensures tumor cell survival in the peripheral system. Although the contribution of epithelial-to-mesenchymal transition to tumor cell invasiveness has been confirmed, the role epithelial-to-mesenchymal transition plays in metastasis remains debated. As a favorable material for a "liquid biopsy", circulating tumor cells have been shown to have promising values in the clinical management of tumors. Furthermore, an increasing number of studies have begun to explore the value of CTC-related biomarkers, and some studies have found that the expression of EMT and stemness markers in circulating tumor cells, in addition to CTC detection, can provide more information on tumor diagnosis, treatment, prognosis and research.
Mining activities, and especially open-pit mines, have a significant impact on the Earth’s surface. They influence vegetation cover, soil properties, and hydrological conditions, both during mining ...and for many years after the mines have been deactivated. Exploring a fast, accurate, and low-cost method to monitor changes, through years, in such an anthropogenic environment is, therefore, an open challenge for the Earth Science community. We selected a case study located in the northeast of Beijing, to assess geomorphic changes related to mining activities. In 2014 and 2016, an unmanned aerial vehicle (UAV) collected two series of high-resolution images. Through the structure-from-motion photogrammetric technique, the images were used to generate high-resolution digital elevation models (DEMs). The assessment of geomorphic changes was carried out by two methodologies. At first, we quantitatively estimated the detectable area, volumetric changes, and the mined tonnage by using the DEM of difference (DoD), which calculated the differences between two DEMs on a cells-by-cells basis. Secondly, the slope local length of autocorrelation (SLLAC) allowed determining the surface covered by open-pit mining by using an empirical model extracting the extent of the open-pit. The analysis of the DoD allows estimating the areal changes and the volumetric changes. The analysis of the SLLAC and its derived parameter allows for the accurate depiction of terraces and the extent of changes within the open-pit mine. Our results underlined how UAVs equipped with high-resolution cameras can be fast, precise, and low-cost instruments for obtaining multi-temporal topographic information, especially when combined with suitable methodologies to analyze the surface geomorphology, for dynamic monitoring of open-pit mines.
Objectives In December 2019, a novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) occurred in Wuhan, China. Laboratory-based diagnostic tests utilized real-time reverse transcriptase ...polymerase chain reaction (RT-PCR) on throat samples. This study evaluated the diagnostic value to analyzing throat and sputum samples in order to improve accuracy and detection efficiency. Methods Paired specimens of throat swabs and sputum were obtained from 54 cases, and RNA was extracted and tested for 2019-nCoV (equated with SARS-CoV-2) by the RT-PCR assay. Results The positive rates of 2019-nCoV from sputum specimens and throat swabs were 76.9% and 44.2%, respectively. Sputum specimens showed a significantly higher positive rate than throat swabs in detecting viral nucleic acid using the RT-PCR assay (p = 0.001). Conclusions The detection rates of 2019-nCoV from sputum specimens were significantly higher than those from throat swabs. We suggest that sputum would benefit for the detection of 2019-nCoV in patients who produce sputum. The results can facilitate the selection of specimens and increase the accuracy of diagnosis.
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